#!/usr/bin/env python3
"""
AI Collaboration Engine - Intelligent Rules V2 Foundation Core
基于 rules/core/ai_collaboration_framework.yaml
"""

from typing import Dict, Any, List, Optional
from enum import Enum
import logging

logger = logging.getLogger(__name__)

class AIRole(Enum):
    """AI角色枚举 - 基于rules定义"""
    PROJECT_MANAGER = "project_manager"
    TECHNICAL_ARCHITECT = "technical_architect"
    DEVELOPER = "developer"
    RULES_DESIGNER = "rules_designer"

class TaskType(Enum):
    """任务类型枚举"""
    ARCHITECTURE_DESIGN = "architecture_design"
    BUSINESS_ANALYSIS = "business_analysis"
    CODE_QUALITY = "code_quality"
    IMPLEMENTATION = "implementation"
    PROJECT_INITIALIZATION = "project_initialization"

class AICollaborationEngine:
    """AI协作引擎 - 4角色智能协作"""
    
    def __init__(self):
        self.current_role = AIRole.PROJECT_MANAGER
        self.context_history = []
        self.role_capabilities = self._init_role_capabilities()
        
    def _init_role_capabilities(self) -> Dict[AIRole, Dict[str, Any]]:
        """初始化角色能力定义 - 基于rules"""
        return {
            AIRole.PROJECT_MANAGER: {
                "strengths": ["项目规划", "需求分析", "团队协调", "进度管理"],
                "responsibilities": ["项目初始化", "需求整理", "里程碑规划"],
                "decision_factors": ["项目复杂度", "团队规模", "时间约束"]
            },
            AIRole.TECHNICAL_ARCHITECT: {
                "strengths": ["架构设计", "技术选型", "系统建模", "性能优化"],
                "responsibilities": ["技术架构", "模块设计", "接口定义"],
                "decision_factors": ["技术复杂度", "可扩展性", "性能要求"]
            },
            AIRole.DEVELOPER: {
                "strengths": ["代码实现", "功能开发", "单元测试", "调试优化"],
                "responsibilities": ["代码编写", "功能实现", "测试用例"],
                "decision_factors": ["实现难度", "代码质量", "开发效率"]
            },
            AIRole.RULES_DESIGNER: {
                "strengths": ["规则设计", "质量保证", "标准制定", "最佳实践"],
                "responsibilities": ["规则制定", "质量检查", "标准化"],
                "decision_factors": ["规则复杂度", "合规要求", "质量标准"]
            }
        }
    
    def select_optimal_role(self, task_type: TaskType, context: Dict[str, Any]) -> AIRole:
        """智能角色选择 - 基于任务类型和上下文"""
        role_mapping = {
            TaskType.PROJECT_INITIALIZATION: AIRole.PROJECT_MANAGER,
            TaskType.ARCHITECTURE_DESIGN: AIRole.TECHNICAL_ARCHITECT,
            TaskType.BUSINESS_ANALYSIS: AIRole.PROJECT_MANAGER,
            TaskType.CODE_QUALITY: AIRole.RULES_DESIGNER,
            TaskType.IMPLEMENTATION: AIRole.DEVELOPER
        }
        
        primary_role = role_mapping.get(task_type, AIRole.PROJECT_MANAGER)
        
        # 基于上下文调整
        complexity = context.get("complexity", 3)
        if complexity >= 4 and task_type == TaskType.ARCHITECTURE_DESIGN:
            primary_role = AIRole.TECHNICAL_ARCHITECT
        
        logger.info(f"🎯 Selected role: {primary_role.value} for task: {task_type.value}")
        return primary_role
    
    def execute_collaboration_workflow(self, workflow_name: str, inputs: Dict[str, Any]) -> Dict[str, Any]:
        """执行协作工作流"""
        workflows = {
            "project_initialization": self._project_initialization_workflow,
            "problem_solving": self._problem_solving_workflow,
            "code_review": self._code_review_workflow
        }
        
        workflow_func = workflows.get(workflow_name)
        if not workflow_func:
            return {"error": f"Unknown workflow: {workflow_name}"}
        
        return workflow_func(inputs)
    
    def _project_initialization_workflow(self, inputs: Dict[str, Any]) -> Dict[str, Any]:
        """项目初始化工作流 - 基于rules定义"""
        results = {
            "workflow": "project_initialization",
            "steps_completed": [],
            "outputs": {}
        }
        
        # Step 1: 架构设计 (Technical Architect)
        self.current_role = AIRole.TECHNICAL_ARCHITECT
        arch_design = {
            "directory_structure": "foundation/modules/coordination架构",
            "module_division": "基于三层协作模式",
            "dependencies": "统一配置管理+规则引擎"
        }
        results["steps_completed"].append("architecture_design")
        results["outputs"]["architecture"] = arch_design
        
        # Step 2: 业务建模 (Project Manager)
        self.current_role = AIRole.PROJECT_MANAGER
        domain_model = {
            "business_rules": "基于intelligent_rules指导原则",
            "data_model": "项目类型+配置+模板",
            "processes": "检测->选择->生成->验证"
        }
        results["steps_completed"].append("domain_modeling")
        results["outputs"]["domain_model"] = domain_model
        
        # Step 3: 实施指导 (Rules Designer)
        self.current_role = AIRole.RULES_DESIGNER
        implementation_guide = {
            "development_standards": "遵循15个rules标准",
            "quality_checklist": "配置管理+防重复+AI协作",
            "collaboration_norms": "4角色协作工作流"
        }
        results["steps_completed"].append("implementation_guidance")
        results["outputs"]["implementation_guide"] = implementation_guide
        
        logger.info(f"✅ Project initialization workflow completed")
        return results
    
    def _problem_solving_workflow(self, inputs: Dict[str, Any]) -> Dict[str, Any]:
        """问题解决工作流"""
        problem = inputs.get("problem", "")
        
        # Step 1: 问题分析 (Rules Designer)
        analysis = {
            "category": "架构问题" if "架构" in problem else "实现问题",
            "impact": "中等",
            "solutions": ["重构", "优化", "补充规则"]
        }
        
        return {
            "workflow": "problem_solving",
            "analysis": analysis,
            "recommended_actions": ["分析根因", "制定方案", "验证效果"]
        }
    
    def _code_review_workflow(self, inputs: Dict[str, Any]) -> Dict[str, Any]:
        """代码审查工作流"""
        code_changes = inputs.get("code_changes", [])
        
        review_results = {
            "automated_checks": "规则验证通过",
            "architecture_review": "架构一致性良好", 
            "quality_assessment": "代码质量符合标准"
        }
        
        return {
            "workflow": "code_review",
            "results": review_results,
            "approved": True
        }
    
    def get_collaboration_status(self) -> Dict[str, Any]:
        """获取协作状态"""
        return {
            "current_role": self.current_role.value,
            "available_roles": [role.value for role in AIRole],
            "context_history_size": len(self.context_history),
            "version": "2.0.0"
        }

# 全局协作引擎实例
_global_collaboration_engine = None

def get_collaboration_engine() -> AICollaborationEngine:
    """获取全局协作引擎实例"""
    global _global_collaboration_engine
    if _global_collaboration_engine is None:
        _global_collaboration_engine = AICollaborationEngine()
    return _global_collaboration_engine

if __name__ == "__main__":
    print("🧪 Testing AI Collaboration Engine V2...")
    engine = AICollaborationEngine()
    
    # 测试项目初始化工作流
    init_result = engine.execute_collaboration_workflow("project_initialization", {
        "project_type": "web",
        "requirements": ["企业级", "高性能", "可扩展"]
    })
    
    print(f"✅ Collaboration test result: {len(init_result['steps_completed'])} steps completed")
    print("🎉 AI Collaboration Engine V2 test completed!")

